GenAI Developer

Job description

Key Responsibilities • Design, develop, and deploy enterprise Generative AI applications using Azure OpenAI Services. • Build Retrieval-Augmented Generation (RAG) pipelines using embeddings and vector databases. • Develop scalable REST APIs using FastAPI and Flask. • Integrate Vision LLMs for image, document, and multimodal understanding. • Build document processing pipelines using PyMuPDF for PDF extraction, parsing, and preprocessing. • Implement semantic search using FAISS Vector Database. • Engineer prompts and optimize LLM responses for enterprise use cases. • Develop AI-powered chatbots, document Q&A, summarization, and intelligent automation solutions. • Optimize AI models for latency, scalability, and cost efficiency. • Integrate AI solutions with enterprise applications and cloud services. • Implement monitoring, evaluation, and experimentation frameworks using Opik or similar LLM observability tools. • Collaborate with product managers, architects, data scientists, and software engineers to deliver AI solutions. • Ensure AI applications follow security, governance, and responsible AI best practices. Required Skills Generative AI • Large Language Models (LLMs) • Prompt Engineering • Retrieval-Augmented Generation (RAG) • Embeddings • Semantic Search • AI Agents • Function Calling • Context Management • Model Evaluation Cloud & AI Platforms • Azure OpenAI Service • Azure AI Services • Azure Cognitive Search (preferred) • Azure Storage • Azure Functions (preferred) Programming • Python (Advanced) • FastAPI • Flask • REST API Development • Async Programming AI Frameworks & Libraries • LangChain • LlamaIndex • PyMuPDF • FAISS Vector Database • Vision LLMs • OpenAI SDK • Transformers (preferred) Development Tools • Visual Studio Code (VS Code) • PyCharm • Git • GitHub/Azure DevOps • Docker Observability & Evaluation • Opik • Prompt evaluation • LLM monitoring • Experiment tracking • Performance benchmarking Required Experience • 5–10 years of software development experience with strong Python expertise. • Minimum 2–4 years of hands-on experience in Generative AI and LLM-based application development. • Experience implementing enterprise RAG architectures. • Strong experience with Azure OpenAI. • Experience integrating Vision LLMs for document and image processing. • Hands-on experience with vector databases such as FAISS. • Experience building production-ready AI APIs using FastAPI or Flask. • Experience processing large PDF/document repositories using PyMuPDF. • Experience with AI evaluation and observability tools such as Opik. • Experience deploying AI applications in cloud environments. Nice-to-Have Skills • LangGraph • AutoGen/CrewAI • Azure AI Search • Cosmos DB • PostgreSQL • Redis • Kubernetes • MLflow • Hugging Face • OCR (Azure Document Intelligence, Tesseract) • CI/CD pipelines • MLOps